The Deep Learning Summit Jan. 25-26th in San Francisco was an outstanding event with exhibitor hall, 3 tracks, workshops, and speakers readily available to have discussions with. One of the best presentations was by Ian Goodfellow on GANs (Ian is on left in the picture below, MIT Executive Education AI student Jovanka Ciric Vujkovic in the center, I am on the right). I was surprised Andrew Ng didn’t present but Ian took the spotlight as the event AI celebrity. Ian had his book signing at the summit Deep Learning MIT Press & on Amazon

With the advent of The Great AI Product Verticalization (see Issue #4), this is a good article to get you started with “AI Sticker” assessment to help in the buy vs. build vs. partner decision making process. It’s good to have an AI business strategy roadmap not to get caught in the AI vendor hype and allow focusing on the problem being solved, the available data, can traditional IT solve the problem, do you need a Machine Learning or Data Science team…?

Last year I researched the competitive landscape for vertical, AI enabled online fraud detection platforms and came up with additional assessment questions related to those provided in the above “How to Know” article:

✔ Is the AI company part of a data consortium?✔ Does your AI product allow customization of their models based on each business select needs?✔ Is there real-time online learning, e.g., if another site reports a related fraud will your system update the fraud score?✔ Which ML/Big Data framework is being used to build their platform. Did they partnered with IBM, Amazon, MS, etc. and white labeled? If not, why did you build vs. partner?

I manage a group of machine learning and data scientist professionals at Everymans.ai, a boutique marketing, and AI enabling consultancy. We help companies quickly exploit marketing opportunities by building AI-enabled Minimum Viable Products (MVP) that will differentiate their products and services to gain a competitive edge with AI.